Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Susquehanna International Group
- UNIVERSITY OF HELSINKI
- University of Utah
- Carnegie Mellon University
- Radix Trading LLC
- UNIVERSIDAD POLITECNICA DE MADRID
- University of Massachusetts Medical School
- Brookhaven National Laboratory
- CNRS
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- Edmund Mach Foundation
- Forschungszentrum Jülich
- Institute for bioengineering of Catalonia, IBEC
- National Renewable Energy Laboratory NREL
- Nature Careers
- Norwegian University of Life Sciences (NMBU)
- RAEGE-Az
- SINTEF
- Tampere University
- Technical University of Munich
- Temple University
- The University of Alabama
- UNIVERSITY OF BUCHAREST
- Universidade de Coimbra
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); Amsterdam
- University of California, Los Angeles
- University of Florida
- University of Newcastle
- University of Texas at El Paso
- University of Toronto
- Université Grenoble Alpes
- Vision Institute
- 23 more »
- « less
-
Field
-
), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
-
, the selected researchers will deal with: Research & Development: Designing, developing, and implementing state-of-the-art machine vision and deep learning algorithms to analyze complex image and sensor data
-
of racial equity in schools, linkages between poverty, social inequality and education, education policy and the academic, social and emotional factors that impact student learning. • Exhibit a deep
-
environment representations, deep reinforcement learning, and intelligent robotic behavior. Solutions will be validated in simulation (e.g., ROS/Gazebo, Isaac Sim) and real robotic platforms. The candidate is
-
Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
-
focus. Example learning problems include exposome and dynamic exposome modeling, learning in timeseries and spatial data, and hybrid deep learning-causal modeling. The successful applicant should have
-
- and electronics- workshops, but also with the NanoLab Amsterdam cleanroom facility situated in the neighboring NWO-institute AMOLF; develop deep-rooted expertise with and maintenance of WZI’s research
-
, multisignal patches and wireless devices. Design and development of algorithms for multimodal biomedical signals based on Personalized Models, Deep Learning and Explainable AI. Applications to respiratory
-
cleanroom facility situated in the neighboring NWO-institute AMOLF; develop deep-rooted expertise with and maintenance of WZI’s research facilities and software packages; be able to act as advisor and expert
-
strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives